The AIDS crisis continues with ca. 40 million people infected by HIV and 2.9 million HIV-related deaths in 2006.1 The virally encoded proteins of HIV provide chemotherapeutic targets for the treatment of infection by the virus. A principal point of attack has been HIV reverse transcriptase (RT), which is required for the conversion of the viral genomic RNA to DNA and for successful infection of host cells. This has led to the development and FDA approval of two important classes of anti-HIV drugs: (i) nucleoside and nucleotide RT inhibitors (NRTIs and NtRTIs), e.g., AZT, ddI, ddC, d4T, FTC, TDF, and 3TC, and (ii) non-nucleoside RT inhibitors (NNRTIs), specifically, nevirapine, delavirdine, efavirenz (Sustiva) and atravirine (TMC125). The NRTIs and NtRTIs are actually faulty substrates that cause premature termination of the growing DNA transcript, while NNRTIs are true inhibitors which bind to an allosteric pocket in the vicinity of the polymerase active site. The therapeutic situation is challenged by rapid mutation of the virus to yield resistant strains. This leads to need for new drugs with activity against at least parts of the spectrum of variants, which are now clinically observed.
The present efforts have been directed at the development of NNRTIs with enhanced therapeutic spectra and auspicious pharmacological properties. The approach to-date has featured focused synthetic organic chemistry and anti-HIV assaying driven by automated procedures for creation and evaluation of virtual libraries, estimation of pharmacological properties, and lead optimization featuring free-energy perturbation calculations to assess relative protein-ligand binding affinities.3 Highly potent and structurally diverse anti-HIV agents have been discovered, however, we continue to seek activity against an ever-wider range of viral mutants and exploration of alternative structural classes for NNRTIs.
To this end, reported successes for lead generation by molecular docking have been intriguing,4 and it was decided to try this approach to seek novel NNRTIs. The following report provides a case study on a common dilemma in a virtual or high-throughput screening exercise. It is demonstrated that with confidence in computed structures and estimated activities, it is possible to convert a false positive into an active agent.